1. 3.4 Modernisation of Social Statistics
DSS Meeting 4-5 March 2013

2. Background Drivers General approach Efficiency gains
Increased responsiveness
General approach
Removal of obstacles
Facilitation of common developments

3. Integrated system of micro-datasets
Core activity: high potential for efficiency gains
Reduction of demands in terms of data precision, joint distributions and frequencies
Preparation for suitability of web-based questionnaires
Preparation for substitution of parts of the data collection by administrative data
Aim:
from a set of separate surveys to a system of interlinked micro-datasets

4. Integrated system of micro-datasets: key elements
Modularity:
Subject matter expertise  Involvement of specialised working groups
Multi-purpose (core modules, common standardised modules)
Issues:
Coherence in terms of terminology and granularity
Forward looking perspective
Modularisation criteria
Re-use of data:
Combining results of different surveys
Boost in accuracy or opportunity to reduce sample size
Issue: Methodological challenges
Targeted design:
Shorter micro-datasets:  higher response rates, suitability for web questionnaires
Larger number of micro-datasets: more flexible joint distributions
Issue: Critical review of user needs in terms of joint distributions and their associated requirements in terms of frequency and precision

5. Integrated system of micro-datasets: key elements
Multi-source nature
Surveys combined with administrative data
Common reference implementation:
Mandatory data specification
Recommended organisation of the system
Programming:
Common programming  role of DSS
In line with EPSS

6. Integrated system of micro-datasets : next steps
For DSS in October 2013:
Outcome of the modularisation
Developing concrete scenarios for integration (illustrating potential gains)
Developing pilots for testing at national level
Legislative issues
Roadmap for development

7. Statistical data matching
Ex post matching faces several challenges
Opportunities arise from statistical matching that is planned ex ante
Statistical matching as a complement to a system of interlinked micro-datasets
Indicators based on an extensive battery of questions
Simplified module with high predictive power and stand-alone capacity
Toolbox of methods

8. Multi-mode data collection /web questionnaires
Drivers
Reduced cost of data collection
Reduced burden on respondents
Growing potential in a context in which the web is increasingly used for contracts with authorities, banking, commerce
ESSnet DCSS (Data collection for social surveys using multiple modes)
Methodological guidance
Possibilities of sharing tools / common developments
Design of the data collection, sampling and estimation process in a mixed mode environment

9. Standardisation of variables and modules
Efficiency gains
Data collection (modularisation of surveys)
Data processing and estimation (matching, linking, data imputation)
Dissemination
Core Social Variables and beyond
More variables and modules
Deeper standardisation of definitions and breakdowns
Not compulsory in all surveys

10. Multisource statistics / Use of administrative data sources
Drivers
Reduced cost of data collection
Reduced burden on respondents
Re-use of information
ESS.VIP Admin (Administrative Data Sources)
Common approaches to tackle risks
Strategic workshop
Steering Group to be put in place

11. ESS.VIP Admin – Strategic Workshop
Key topics
Development of a quality framework
Quality of input and metadata
Common concepts
Data linkage
Imputations and estimation
Role of NSIs in administrative data collection process
Confidentiality and data protection
EU legislation
Sharing best practices
Financial resources
Commercial data